Product inspection policy for an imperfect production system with inspection errors and warranty cost

Sarkar, Biswajit; Saren, Sharmila

doi:10.1016/j.ejor.2015.06.021

Cited by 147 publications

(63 citation statements)

References 42 publications

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“…The shifting time point s is a random variable, with the probability density function

f (s)

and cumulative distribution function

F (s)

. According to the previous research, the shifting time point s follows an exponential distribution (Ben‐Daya et al., ; Chung et al., ; Jeang, ; Sarkar and Saren, ). The probability density function is

f false(s false) = e^{- s / λ} / λ

.…”

Section: Assumptions and Notationmentioning

confidence: 97%

“…In order to help companies deal with the inventory problems subject to production process unreliability, a lot of inventory models are studied. In most of the studies on EPQ models, people treat the production line reliability as an exogenous factor and mainly concern about the scheduling, inventory, or marketing problems (Ben‐Daya et al., ; Chung et al., ; Jeang, ; Sarkar and Saren, ). However, in real industry, to mitigate the negative effects (e.g., raw material shortage, quality defect, or productivity losses) on production line unreliability, companies have strong incentives to improve their production line reliability by investing in high‐quality machines, high‐skilled workers, or advanced maintenance technologies (http://www.lce.com/Introduction_to_Reliability_Excellence_Rx_78-item.html).…”

Section: Introductionmentioning

confidence: 99%

“…Atan and Snyder () studied the EOQ models considering disruptions. Sarkar and Saren () studied a more general model in which the defective rate in the in‐control state is nonzero, then, in the out‐of‐control state, the defective rate rises. They also take the inspection errors and warranty cost into consideration.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

EPQ for an unreliable production system with endogenous reliability and product deterioration

Huang

2016

Int Trans Operational Res

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In this paper, we study an economic production quantity problem for a production line subject to random shift from the in-control state (with high production rate) to out-of-control state (with low production rate). Different from previous research, we model the expected shift time as a controllable variable, based on the fact that, by investment in resources, the reliability of the production line can be improved. In the mathematical model, we consider three possible scenarios: no shift, shift without demand shortage, and shift with demand shortage, which are determined by the values of actual shift time and shifted production rate. Combining the three possible scenarios, the goal is to minimize the expected total cost per unit time by finding the optimal production time, as well as the optimal expected shift time. In addition, we extend the model to deterioration products and study the influence of product deterioration to the optimal decisions. Numerical examples are presented to illustrate the optimal solutions, followed by the sensitive analysis on important parameters. Comparing the optimal solutions under no reliability investment, reliability investment can help companies save more cost. Some other managerial insights are also proposed based on the numerical tests.

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“…The shifting time point s is a random variable, with the probability density function

f (s)

and cumulative distribution function

F (s)

f false(s false) = e^{- s / λ} / λ

.…”

Section: Assumptions and Notationmentioning

confidence: 97%

Section: Introductionmentioning

confidence: 99%

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EPQ for an unreliable production system with endogenous reliability and product deterioration

Huang

2016

Int Trans Operational Res

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“…For the latter, they used the order overlapping approach as used in Maddah [18] to explore both cases with imperfect quality and imperfect screening scenarios. In this direction, Sarkar and Saren [32] developed an improved inspection policy for the production model.…”

Section: Inspection Plansmentioning

confidence: 99%

Inventory and pricing decisions for imperfect quality items with inspection errors, sales returns, and partial backorders under inflation

et al. 2020

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In this paper, an optimal replenishment inventory policy for imperfect quality items is presented with a selling price-dependent demand under inflationary conditions using a discounted cash flow (DCF) approach. Due to the presence of defectives in the system, all items go through a 100% inspection process. However, the screening process is also considered to be imperfect and involves errors, namely Type-I and Type-II. In addition, shortages are allowed and are partially backlogged. An optimal solution for the proposed model is derived by maximizing the expected profit function by jointly optimizing three decision variables: selling price, order quantity, and backorder level. To validate the theoretical results, a numerical example along with comprehensive sensitivity analysis is offered. The model has pertinence in industries like

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“…However, they assumed that inspection consumed a negligible time. Chang et al [31], Sarkar and Saren [32], and Zhou et al [33] are some, just to name few, who contributed to the same direction in the recent past.…”

Section: Introductionmentioning

confidence: 99%

Human errors incorporation in work-in-process group manufacturing system

2017

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KEYWORDSHuman error Type I; Human error Type II; Group-technology; Optimal lot size.Abstract. Decisions, about product acceptance or rejection, based on technical measurement report in ultra-precise and high-tech manufacturing environment is highly challenging as product reaches nal stage after high value-added processes. Moreover, the role of technical personnel in decision making process for inventory models with focus on group-technology manufacturing setup has been considered relatively less. Most of the literature assumes that decisions are perfect and error free. However, in reality, human errors exist in making such decisions based on measurement reports. This paper incorporates human errors into the decision making process focusing on group-technology inventory model, where high value-added machining processes are involved. Therefore, a mathematical model is developed for the optimal lot size considering human errors in the decision making process and the imperfect production process with focus on work-inprocess inventory. Lot size is optimized based on average cost minimization by incorporating human error Type I and human error Type II. Numerical examples are used to illustrate and compare the proposed model with the previously developed models for group-technology high-tech manufacturing setups. The proposed model is considered more exible as it incorporates imperfection in process with human errors in decision making process.

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Product inspection policy for an imperfect production system with inspection errors and warranty cost

Cited by 147 publications

References 42 publications

EPQ for an unreliable production system with endogenous reliability and product deterioration

EPQ for an unreliable production system with endogenous reliability and product deterioration

Inventory and pricing decisions for imperfect quality items with inspection errors, sales returns, and partial backorders under inflation

Human errors incorporation in work-in-process group manufacturing system

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